Upload README.md with huggingface_hub
Browse files
README.md
ADDED
|
@@ -0,0 +1,35 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: mit
|
| 3 |
+
tags:
|
| 4 |
+
- infinite-dataset-hub
|
| 5 |
+
- synthetic
|
| 6 |
+
---
|
| 7 |
+
|
| 8 |
+
# ResourceAllocationChallenges
|
| 9 |
+
|
| 10 |
+
tags: Optimization, Operations Research, Industry Data
|
| 11 |
+
|
| 12 |
+
_Note: This is an AI-generated dataset so its content may be inaccurate or false_
|
| 13 |
+
|
| 14 |
+
**Dataset Description:**
|
| 15 |
+
|
| 16 |
+
The 'ResourceAllocationChallenges' dataset comprises of anonymized case studies from various industries facing resource allocation issues that align with the keywords 'Optimization, Operations Research, Industry Data'. Each entry captures a unique challenge related to the allocation of resources (financial, human, physical, etc.) within a company's operations and outlines the context, actions taken, and outcomes. The focus is on situations where companies are trying to optimize their resource distribution to overcome their challenges effectively. The dataset can be used for analysis and training machine learning models aimed at predicting optimal resource allocation strategies.
|
| 17 |
+
|
| 18 |
+
**CSV Content Preview:**
|
| 19 |
+
|
| 20 |
+
```
|
| 21 |
+
"case_id","challenge_description","sector","action_taken","outcome","label"
|
| 22 |
+
"RAG001","Difficulty in balancing budget constraints with operational needs in a tech startup","Technology","Implemented a dynamic resource allocation model","Improved financial efficiency by 20%","Optimization"
|
| 23 |
+
"RAG002","Inadequate workforce distribution causing bottlenecks in production","Manufacturing","Introduced cross-training and flexible staffing","Reduced production time by 15%","Operations Research"
|
| 24 |
+
"RAG003","Lack of coordination between supply chain and marketing leading to overstock","Retail","Launched a centralized planning system","Decreased inventory waste by 25%","Resource Allocation"
|
| 25 |
+
"RAG004","Struggle with real-time resource adjustments during peak demand","Service","Adopted predictive analytics for resource forecasting","Increased customer satisfaction scores","Industry Data"
|
| 26 |
+
"RAG005","Challenges in integrating new technology with existing processes","Healthcare","Conducted an in-depth workflow analysis","Streamlined patient care process","Resource Allocation"
|
| 27 |
+
```
|
| 28 |
+
|
| 29 |
+
**Source of the data:**
|
| 30 |
+
|
| 31 |
+
The dataset was generated using the [Infinite Dataset Hub](https://huggingface.co/spaces/infinite-dataset-hub/infinite-dataset-hub) and microsoft/Phi-3-mini-4k-instruct using the query 'RAG':
|
| 32 |
+
|
| 33 |
+
- **Dataset Generation Page**: https://huggingface.co/spaces/infinite-dataset-hub/infinite-dataset-hub?q=RAG&dataset=ResourceAllocationChallenges&tags=Optimization,+Operations+Research,+Industry+Data
|
| 34 |
+
- **Model**: https://huggingface.co/microsoft/Phi-3-mini-4k-instruct
|
| 35 |
+
- **More Datasets**: https://huggingface.co/datasets?other=infinite-dataset-hub
|